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Partner Engagement Webinar Series: Highlights from DataFest North America

Denodo
Denodo

Watch full webinar here: https://buff.ly/3tCksyw Watch this webinar for a recap of the highlights from DataFest 2023 North America, including an exploration of the latest innovations in logical data management with Denodo. During this one-hour session, Mark Miller, Vice President of Global SI, Partners, and Channel Sales North of America, and Inessa Gerber, Director of Product Marketing, will guide us through a discussion of the most recent product information and critical updates you can’t afford to miss. Maximize your knowledge of the Denodo Platform, increase ROI on Denodo data and analytics tools, and elevate your success in the Denodo Partner Program.

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Partner Engagement Webinar Series: Highlights from DataFest North America
Partner Engagement Webinar Series: Highlights from DataFest North America
Thank you to our Partner Sponsors
Highlights – Denodo Datafest 2023
Partner Engagement Webinar Series: Highlights from DataFest North America
Partner Engagement Webinar Series: Highlights from DataFest North America

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Partner Engagement Webinar Series: Highlights from DataFest North America

  • 3. Thank you to our Partner Sponsors
  • 4. Highlights – Denodo Datafest 2023
  • 7. Collaboration – Not Competition
  • 8. Copyright © 2019 HCL Technologies Limited | www.hcltech.com
  • 10. Unleashing the Power of Denodo Platform: Product Highlights Director of Product Management (NA) Inessa Gerber
  • 11. Agenda 11 1. Deployment Strategies for Hybrid/Multi-Cloud ▪ Denodo as part of Cloud Migration Journey ▪ Denodo Hybrid/Multi-Cloud Deployment ▪ FinOps and data adoption/utilization 2. Data Management Collaboration (e.g., Data Lakes) ▪ Complementary Technology with ETL/ELT ▪ Optimized Access with Embedded MPP based on Presto 3. Data Governance ecosystem ▪ Inventory & Consumer Data Catalogs ▪ Data Governance and Data Security
  • 14. 14 Cloud Deployment Models Source: Denodo Global Cloud Survey 2022
  • 15. 15 Cloud Migration Journey: Reroute Data Pipelines
  • 16. 16 Cloud Migration Journey: Introduce Abstraction Layer
  • 17. 17 Cloud Migration Journey: Repoint Consumers to Denodo
  • 18. 18 Cloud Migration Journey: Denodo access to Cloud Sources
  • 19. 19 Cloud Migration Journey: Repoint Consumers to all Migrated Data
  • 20. 20 Cloud Migration Journey: Migration Complete
  • 21. 21 Cloud Migration Journey: Evolve Architecture and Accommodate
  • 22. 22 Hybrid Deployment (e.g., AWS) ▪ Local Authentication Realm / Policies ▪ Minimize Network Traffic with relevant data ▪ Optimize access with local Summaries/Cache ▪ Future proof flexible architecture ▪ Transparent to the consumer ▪ Centrally managed with Denodo Solution Manager
  • 24. 24 Key Features: Automated Deployment Centralized Management and Monitoring with Denodo Solution Manager. Automated Deployment for AWS/Azure, CI/CD capabilities, and streamlined deployment.
  • 25. 25 Key Features: FinOps - Visibility is Key Data sources can be assigned to an CSP/on- prem and a region. This allows Denodo to calculate and aggregate egress traffic in bytes Log information on Traffic between locations (egress costs), execution times and scanned bytes at data sources
  • 26. 26 Key Features: FinOps - Visibility is Key New dashboards allow for analysis of those metrics, slicing and dicing by source, consumer, ISV and region, to understand evolution of critical cost metrics
  • 27. Data Management: Data Lakes, Lake Houses, and more…
  • 28. 28 All My Data is Centralized… ➢ ▪ ▪ ▪ ▪ ▪
  • 29. 29 Realistic Expectations ▪ ▪ ▪ ▪ ▪ Gartner, Magic Quadrant for Data Integration Tools August 2021 Ehtisham Zaidi, et al Gartner, The Practical Logical Data Warehouse December 2020 Henry Cook, et al
  • 30. 30 Looking at Snowflake and alike… ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ https://www.denodo.com/en/document/whitepaper/modern-data-strategy-denodo-and-snowflake
  • 31. 31 Key Features: Denodo Embedded MPP Engine ▪ Denodo has embedded its own MPP engine, based on Presto ▪ Scalable performance for big data volumes ▪ Easy and efficient access to data lake content ▪ Out-of-the-box MPP options for caching and query acceleration ▪ Native autoscaling ▪ Graphical browsing and introspection of object storage ▪ S3, ADLS, HDFS, etc. ▪ Integrated data lake management ▪ Security, data ingestion, ELT flows, curation, etc.
  • 32. 32 Key Features: Denodo Architecture with MPP ▪ Denodo’s embedded MPP is included in Enterprise Plus ▪ The maximum size of the cluster, measured as Presto CPUs, is 128 x the cores of the VDP server ▪ 8 cores in VDP = (8 x 128) 1024 cores in Presto ▪ 16 cores in VDP = (16 x 128) 2048 cores in Presto
  • 33. 33 Key Features: Support for ETL/ELT ▪ Flexible option to replicate any Denodo view or table to any target location ▪ ETL when source and target are in different locations. (e.g. replicate mongoDB data into Data Lake) ▪ ELT execution (SELECT INTO commands) when source and target the same (e.g. zones in a Data Lake)
  • 35. 35 Denodo Data Catalog Bridges the Gap between IT and Business ▪ Marketplace for Data Products and streamlined data shopping experience minimizes data discovery time allowing for faster business insights, while making relevant data accessible on demand. ▪ Guided Data Discovery ▪ AI-driven recommendations for critical and related data sets ▪ Business metadata for organizing and contextualizing data assets across the organization ▪ Collaboration and governance features fostering teamwork ▪ Trusted Data with Data Lineage, Usage Statistics, and Profiling ▪ Fully Integrated with Delivery Layer ▪ Always in synch with underlying Denodo Platform ▪ Integrated governance, data access, and data masking ▪ Collaboration between Business using DC and Developers using Design Studio Denodo Proprietary and Confidential
  • 36. 36 Data Catalog: Search and Discovery ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪
  • 37. 37 Data Cataloging and Data Governance ▪ Denodo is a Data Virtualization and Delivery Layer ▪ Focus on Data Delivery, Data Access, and Data Management across the enterprise ▪ Targeting Self-Service initiatives for BI Analysts, Data Scientists, Data Citizens who need data access ▪ Key Focus on Security, Semantic Modeling, Performance and Centralized Access Controls ▪ Enterprise Data Governance Tools (e.g., Collibra, IGC, etc…) ▪ Focus on data inventory, stewardship, trustworthiness and quality, etc. ▪ Targeting Data Stewards and CDOs who need to manage the data ▪ Collaboration and Complementary approach ▪ Other tools can ingest Denodo tables, views, lineage, etc.. Using Denodo Governance bridge or scanners ▪ Denodo can also ingest tags (data classification) from external DG tools
  • 38. 38 Tags Metadata Denodo + Collibra: Collaboration Denodo Views (Semantic Models) can be consumed directly by users & can be shared with DG/DC tools After Synchronization, Denodo Metadata is available in Collibra Lineage gathered from Denodo Derived Views and Relationships Import data classification (tags) from Collibra into Denodo
  • 39. 39 Key Features: Global Security Policies ▪ Tags are available on column and view level to easily identify and classify data ▪ Tags can be imported from external tools, such as Collibra and others ▪ Allows for implementation of semantic-driven access controls across the data landscape
  • 40. 40 Key Features: Global Security Policies ▪ Global Policies are based on the Semantics using the tags instead of data artifacts ▪ Completely abstracted from specific tables ▪ Easier to manage and less error prone ▪ E.g mask the contact information such as #email or #sensitive with *** for Data Scientist ▪ E.g. mask #SSN tagged data for non-HR ▪ E.g. mask #sensitive data for users coming in from external IP addresses (ABAC) ▪ Supports RBAC and ABAC ensuring extended flexibility for diverse use-cases ▪ Extended masking based on data types and support for customizations
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